Traditional ML courses and the projects you do as part of it are not meant for engineers.
As a mechanical engineer or a physicist, why would I do a project on movie review analyzer or housing price prediction?
I would love to do a project which teaches me how to use ML to model fluid mechanics or black hole dynamics.
I want a field which combines ML with my domain knowledge.
Scientific ML is exactly that field.
I feel Scientific ML is one of the coolest techniques of the last 4-5 years.
There are 3 main pillars of Scientific ML:
(1) Neural ODEs
(2) Physics Informed Neural Networks (PINNs)
(3) Universal Differential Equations
It helped me transition from mechanical engineering to machine learning, and obtain a PhD at MIT in Machine Learning.
Any thoughts on Scientific ML or PINNs or Neural ODEs?
